We report in tab:modules-metrics the obtained results in terms of mae and rmse. It is worth noting that, as a result of the squaring operation, rmse effectively penalizes large errors more heavily than small ones, thus more suitable when outliers are particularly undesirable. Furthermore, we also compute the ssim [1]} to measure the density map quality, which measures images' similarities under three aspects: brightness, contrast, and structure. The value of ssim is in the \([0, 1]\)  range: the larger it is, the less distortion of the image is measured (see also sec:back:visual-counting:metrics for further details). Finally, in fig:crowdcounterdensityoutputexamples we show some examples of the considered images, together with the ground truth and the predicted density maps.
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